Method for detecting potential falls and a fall detector

ABSTRACT

There is provided a fall detector for detecting a potential fall by a user, the fall detector comprising a sensor for measuring the skin conductivity of the user; and a processor for analyzing the skin conductivity measurements to determine whether the user has had a potential fall, wherein the processor is configured to analyze the skin conductivity measurements by matching the skin conductivity measurements to a predetermined skin conductivity response corresponding to a stressful event.

TECHNICAL FIELD OF THE INVENTION

The invention relates to a method for detecting potential falls by auser and a fall detector, and in particular relates to a method fordetecting a potential fall and a fall detector that provides increasedfall detection reliability.

BACKGROUND TO THE INVENTION

Falls affect millions of people each year and result in significantinjuries, particularly among the elderly. In fact, it has been estimatedthat falls are one of the top three causes of death in elderly people. Afall is defined as a sudden, uncontrolled and unintentional downwarddisplacement of the body to the ground, followed by an impact, afterwhich the body stays down on the ground.

Personal Help Buttons (PHBs) are available that require the user to pushthe button to summon help in an emergency. However, if the user suffersa severe fall (for example if they are knocked unconscious), the usermight be unable to push the button, which might mean that help doesn'tarrive for a significant period of time, particularly if the user livesalone.

Fall detectors are also available that process the output of one or moremovement sensors to determine if the user has suffered a fall. Mostexisting body-worn fall detectors make use of an accelerometer (usuallyan accelerometer that measures acceleration in three dimensions) andthey try to infer the occurrence of a fall by processing the time seriesgenerated by the accelerometer. Some fall detectors can also include anair pressure sensor, for example as described in WO 2004/114245. Ondetecting a fall, an alarm is triggered by the fall detector.

Some fall detectors are designed to be worn as a pendant around the neckof the user, whereas others are designed to be worn on the torso orlimbs of the user, for example at the wrist. However, the wrist iscapable of complex movement patterns and has a large range of movement,which means that existing fall detection methods based on analyzingmeasurements from an accelerometer do not provide a sufficiently highdetection rate while minimizing the number of false alarms for this typeof fall detector.

Therefore, there is a need for an improved method for detecting apotential fall and a fall detector implementing the same.

SUMMARY OF THE INVENTION

According to a first aspect of the invention, there is provided a falldetector for detecting a potential fall by a user, the fall detectorcomprising a sensor for measuring the skin conductivity of the user; anda processor for analyzing the skin conductivity measurements todetermine whether the user has had a potential fall, wherein theprocessor is configured to analyze the skin conductivity measurements bymatching the skin conductivity measurements to a predetermined skinconductivity response corresponding to a stressful event.

In a preferred embodiment, the processor is configured to generate skinconductivity coefficients by matching the skin conductivity measurementsto a predetermined skin conductivity response corresponding to astressful event, the value of each coefficient indicating the match tothe predetermined skin conductivity response, and wherein the processoris configured to determine whether the response is consistent with auser having had a fall by analyzing the skin conductivity coefficients.

In an embodiment, the processor is configured to analyze the skinconductivity coefficients to determine whether the response isconsistent with a user having had a fall by determining one or more of(i) the maximum value of the coefficients, (ii) the mean of thecoefficients, and/or (iii) the median of the coefficients.

In some embodiments, the processor is configured to filter the skinconductivity measurements to remove noise and/or interference prior tomatching the skin conductivity measurements to the predetermined skinconductivity response.

In those embodiments, the processor is preferably configured to use amedian filter to remove the noise and/or interference from the skinconductivity measurements.

In preferred embodiments, the fall detector further comprises at leastone movement sensor for sensing the movement of the user, the processorbeing further configured to analyze measurements from the at least onemovement sensor to determine if the user may have fallen.

In a preferred embodiment, the processor is configured to analyze theskin conductivity measurements only in the event that the measurementsfrom the at least one movement sensor indicate that the user may havefallen.

Preferably, the processor is configured to use the skin conductivitysensor to measure the skin conductivity in the event that themeasurements from the at least one movement sensor indicate that theuser may have fallen.

In embodiments of the invention, the processor is configured to analyzethe measurements from the at least one sensor to identify whether animpact and/or a change in altitude greater than respective thresholdvalues have occurred.

Preferably, the processor is configured to analyze the skin conductivitymeasurements obtained during a time window following a time at which themeasurements from the at least one sensor indicate that the user mayhave fallen.

According to a second aspect of the invention, there is provided amethod of detecting a potential fall by a user, the method comprisingmeasuring the skin conductivity of the user and analyzing the skinconductivity measurements to determine whether the user has had apotential fall by matching the skin conductivity measurements to apredetermined skin conductivity response corresponding to a stressfulevent.

In a preferred embodiment, the step of analyzing comprises analyzingskin conductivity coefficients generated from matching the skinconductivity measurements to the predetermined skin conductivityresponse, the value of each coefficient indicating the match to thepredetermined skin conductivity response.

In an embodiment, analyzing the skin conductivity coefficients todetermine whether the response is consistent with a user having had afall comprises determining one or more of (i) the maximum value of thecoefficients, (ii) the mean of the coefficients, and/or (iii) the medianof the coefficients.

In some embodiments, the method further comprises the step of filteringthe skin conductivity measurements to remove noise and/or interferenceprior to matching the skin conductivity measurements to thepredetermined skin conductivity response.

In those embodiments, the method preferably comprises using a medianfilter to filter the skin conductivity measurements to remove the noiseand/or interference from the skin conductivity measurements.

In preferred embodiments, the method further comprises the steps ofsensing the movement of the user and analyzing the movement of the userto determine if the user may have fallen.

Preferably, the step of analyzing the skin conductivity measurements isperformed only in the event that the step of analyzing the movement ofthe user indicates that the user may have fallen.

In preferred embodiments, the step of measuring the skin conductivity isperformed only in the event that the step of analyzing the movement ofthe user indicates that the user may have fallen.

In embodiments of the invention, the step of analyzing the movement ofthe user comprises determining whether an impact and/or a change inaltitude greater than respective threshold values have occurred.

Preferably, the step of analyzing skin conductivity measurementscomprises analyzing skin conductivity measurements obtained during atime window following a time at which the movements of the user indicatethat the user may have fallen.

According to a third aspect of the invention, there is provided acomputer program product comprising computer readable code embodiedtherein, the computer readable code being configured such that, uponexecution by a suitable computer or processor, the computer or processorperforms the method described above.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the invention will now be described, by way ofexample only, with reference to the following drawings, in which:

FIG. 1 is a block diagram of a fall detector in accordance with theinvention;

FIG. 2 is a flow chart illustrating a method of detecting falls inaccordance with an embodiment of the invention;

FIG. 3 is a flow chart illustrating the analysis of skin conductivitymeasurements according to an embodiment of the invention;

FIGS. 4( a)-(d) are a series of graphs illustrating the skinconductivity measurements and the results of the processing steps shownin FIG. 3;

FIG. 5 is a graph illustrating the filter used in step 1095 of themethod shown in FIG. 3; and

FIG. 6 is a graph illustrating an analysis window for the skinconductivity coefficients determined from the method shown in FIG. 3.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

A fall detector 2 according to an embodiment of the invention is shownin FIG. 1. In a preferred embodiment of the invention, the fall detector2 is designed to be worn by a user on their wrist, although it will beappreciated that the invention is not limited to this use, and the falldetector 2 could instead be designed to be worn at the user's waist, ontheir chest or back or as a pendant around their neck or carried intheir pocket.

In this exemplary embodiment, the fall detector 2 comprises two movementsensors—an accelerometer 4 and pressure sensor 6—which are connected toa processor 8. The processor 8 receives measurements from the movementsensors 4, 6, and processes the measurements to determine if a user ofthe fall detector 2 has suffered a fall. Although two movement sensorsare shown in this embodiment, it will be appreciated that fall detectorsaccording to alternative embodiments may comprise only one movementsensor (for example just the accelerometer 4).

The fall detector 2 further comprises an audible alarm unit 10 that canbe activated by the processor 8 in the event that the processor 8determines that the user has suffered a fall. The fall detector 2 mayalso be provided with a button (not shown in FIG. 1) that allows theuser to manually activate the audible alarm unit 10 if they requireassistance (or deactivate the alarm if assistance is not required).

The fall detector 2 also comprises a transmitter unit 12 that allows thefall detector 2 to transmit an alarm signal to a base station associatedwith the fall detector 2 (which can then issue an alarm or summon helpfrom a healthcare provider or the emergency services) or directly to aremote station (for example located in call centre of a healthcareprovider) if a fall is detected, so that assistance can be summoned forthe user. In some embodiments, the processor 8 in the fall detector 2may not execute the algorithm on the data from the sensors 4, 6 todetermine if the user has fallen; instead the processor 8 andtransmitter unit 12 may provide the raw data from the sensors 4, 6 tothe base station and a processor in the base station can execute thealgorithm on the data from the sensors 4, 6 to determine if the user hasfallen.

As existing fall detection methods based on analyzing measurements froman accelerometer in a wrist-worn fall detector do not provide asufficiently high detection rate while limiting the number of falsealarms, the fall detector 2 according to some aspects of the inventionfurther comprises a sensor 14 for measuring the conductivity of theuser's skin and the processor 8 is configured to analyze the skinconductivity measurements in conjunction with the measurements from themovement sensors 4, 6 to provide a more reliable indication of whetherthe user has suffered a fall. In a wrist-worn fall detector 2, the skinconductivity sensor 14 is preferably arranged to contact the skin of theuser on the volar side of their wrist. In some embodiments, the falldetector 2 comprises multiple skin conductivity sensors 14 that are tobe placed at different positions on the user's body. In this case, atleast one of those skin conductivity sensors 14 can be integrated into aseparate housing to the rest of the components of the fall detector 2.

In the illustrated embodiment, all of the components of the falldetector 2 are integrated into a single housing that is to be placed incontact with the user's skin. In alternative embodiments, for examplewhere part of the fall detector is in the form of a pendant to be wornaround the user's neck (and so might not be in contact with the user'sskin at all times), the skin conductivity sensor 14 can be provided in ahousing that is separate from the pendant (the pendant including theaccelerometer 4 and pressure sensor 6), so that the skin conductivitysensor 14 can be located in contact with the user's skin during use.

The operation of the fall detector 2 will now be described in moredetail with reference to the flow chart in FIG. 2.

In order for the processor 8 in the fall detector 2 (or, in thealternative embodiment described above, for the processor in the basestation) to determine if the user has suffered a fall, it is necessaryto extract values for various features that are associated with a fallfrom the movement sensor measurements. Thus, in step 101, theaccelerometer 4 and air pressure sensor 6 measure the accelerations andair pressure changes experienced by the fall detector 2 and thesemeasurements are provided to the processor 8 by the sensors 4, 6, andthe processor 8 analyses them to determine whether the user might havesuffered a fall (step 103).

A fall can be broadly characterized by, for example, a change inaltitude of around 0.5 to 1.5 meters (the range may be differentdepending on the part of the body that the fall detector 2 is to beworn), culminating in a significant impact, followed by a period inwhich the user does not move very much. Thus, conventionally, in orderto determine if a fall has taken place, the processor 8 needs to processthe sensor measurements to extract values for features including achange in altitude (which is usually derived from the measurements fromthe pressure sensor 6, but can also or alternatively be derived from themeasurements from the accelerometer 4), a maximum activity level (i.e.an impact) around the time that the change in altitude occurs (typicallyderived from the measurements from the accelerometer 4) and a period inwhich the user is relatively inactive following the impact (againtypically derived from the measurements from the accelerometer 4). Itwill be appreciated that other features can further improve thedetection algorithm. For example, the detection of a change inorientation upon falling can improve the likelihood that the signal isdue to a fall.

The analysis performed by the processor 8 in step 103 will not bedescribed in further detail herein, but those skilled in the art will beaware of various algorithms and techniques that can be applied todetermine whether a user may have suffered a fall from accelerometerand/or pressure sensor measurements.

If the processor 8 determines that a user may have suffered a fall (step105), i.e. if the analysis of the accelerometer 4 and/or pressure sensor6 measurements indicates that a fall has taken place, then measurementsof the skin conductivity of the user are taken by the skin conductivitysensor 14 (step 107). If the processor 8 has not detected a possiblefall, the process returns to step 101 and further measurements are takenand analyzed (step 103).

In some embodiments, the skin conductivity sensor 14 is only activatedonce a possible fall (or simply a change in altitude of at least 0.5 mdetected in the measurements from the pressure sensor 6) has beendetected from the analysis of the accelerometer 4 and/or pressure sensor6 measurements, thus reducing the power consumption of the fall detector2. As the analysis in step 103 is performed by the processor 8substantially in real time or with only a small delay, the skinconductivity sensor 14 will be activated shortly after a fall event hasoccurred.

In alternative embodiments, the skin conductivity sensor 14 may measureskin conductivity constantly or frequently whenever the fall detector 2is in use (i.e. even when a possible fall has not yet been detected).This way, skin conductivity measurements will be available to theprocessor 8 as soon as a possible fall is detected.

In step 109, the processor 8 analyses the measurements from the skinconductivity sensor 14 for characteristics associated with a fall. Inparticular, the processor 8 analyses the measurements to identifywhether there has been a measurable skin conductivity response that isconsistent with the user having suffered a stressful event, such as anaccidental fall. In the alternative embodiment described above where theskin conductivity sensor 14 is measuring skin conductivity constantly orfrequently, the processor 8 may analyze the skin conductivitymeasurements only when a possible fall or change in altitude greaterthan a predetermined amount, for example 0.5 m, has been detected fromthe analysis of the measurements from the movement sensor(s) 4, 6.Alternatively, the processor 8 may analyze the skin conductivitymeasurements for a response consistent with the user experiencing astressful event, such as suffering a fall, regardless of whether apossible fall or change in altitude greater than 0.5 m has been detectedyet.

When a person accidentally falls, the process of falling, from losingbalance to the impact with the ground and the (possible) inability toget up after the fall, causes a measureable change in the skinconductivity of the user as a result of the stress suffered by the user.However, a movement, such as sitting down or intentionally ‘falling’onto a chair, which might appear to be a fall from an analysis of theaccelerometer 4 and pressure sensor 6 measurements alone, would notcause this stress response, and the skin conductivity measurements canbe used to qualify whether an accidental fall has taken place.

Thus, the analysis by the processor 8 in step 109 aims to identify askin conductivity response associated with a stressful event (i.e. anaccidental fall) from the measurements obtained after (and in someembodiments, during) the possible fall event. The skin conductivitymeasurements analyzed in step 109 may relate to a period of around 15seconds after the possible fall event has occurred, although thoseskilled in the art will appreciate that time windows having differentlengths can be used.

In step 111, the processor 8 uses the result of the analysis of the skinconductivity measurements and the result of the analysis of theacceleration and air pressure measurements to determine if the user haspotentially suffered a fall. If the user is determined to have fallen,the processor 8 can trigger an alarm to obtain help for the user (step113), as described above. After triggering the alarm, the process canreturn to step 101 to continue the monitoring of the user. If it isdetermined in step 111 that the user has not fallen, the process alsoreturns to step 101 to continue the monitoring of the user.

It will be appreciated that the results of the analysis steps (steps 103and 109) can be combined in a number of different ways. For example,where the skin conductivity sensor 14 is only activated once a possiblefall has been detected, a fall may be determined in step 111 if the skinconductivity measurements are consistent with a fall having taken place.Alternatively, features (such as an impact, altitude change, skinconductivity response) can be extracted from the sensor measurements,and the features combined (possibly using weightings for each extractedfeature) to determine whether a fall has taken place.

In the event that the measurements from the skin conductivity sensor 14indicate that the sensor 14 is not in contact with the user's skin, i.e.the measurements are very low or zero (for example if the fall detector2 is not being worn properly or if the sensor 14 has been knocked out ofposition by the fall), the processor 8 can take a decision on whether aperson has fallen just based on the measurements from the accelerometer4 and/or pressure sensor 6.

The analysis of the skin conductivity measurements by the processor 8 instep 109 of FIG. 2, will now be described in more detail with referenceto the flow chart in FIG. 3, and the graphs shown in FIGS. 4, 5 and 6.

In step 1091, the processor 8 receives the skin conductivitymeasurements. An exemplary set of measurements is shown in FIG. 4( a).The skin conductivity is measured in micro Siemens, μLS.

Firstly, the processor 8 filters the skin conductivity measurements toremove noise and interference (step 1093). The interference may resultfrom electrical interference in the circuitry of the fall detector 2,poor contact between the skin conductivity sensor 14 and the user'sskin, etc.). Preferably step 1093 comprises applying a median filter tothe sensor measurements. The result of the filtering step is illustratedin FIG. 4( b), and it can be seen that spike in the measurements ataround time=550 seconds has been removed.

Then, in step 1095, the filtered skin conductivity measurements arematched to a predetermined pattern corresponding to a skin conductivityresponse associated with a (any) stressful event, such as an accidentalfall, using a matched filter. The output is a set of coefficients thatindicate the match of the measurements to the pattern. Each coefficientrepresents the match of a number of consecutive measurement samples(covering a time period of the same length as the predetermined pattern)to the predetermined pattern. The higher the coefficient, the better thematch of the measurements to the pattern (and therefore the greater thechance that a stressful event, including a fall, has occurred).

In one embodiment, this step is implemented using a matched filter thatis DC-free. This means that the DC component in the measurements fromthe skin conductivity sensor 14 will not adversely affect the filtering,which will produce a ‘0’ skin conductivity coefficient for non-variant(or very low variant) skin conductance.

An exemplary predetermined pattern, i.e. impulse response of the matchedfilter, that represents the skin conductivity response that would bemeasured at the wrist of a person who suffers a fall or other suddenstress-inducing event can be given by the function

match_(—) filter=A(t ^(n) =B)e ^(−t/τ) −DC _(remove)   (1)

where t is time (0≦t≦30), A is a scaling factor that determines theheight of the initial part of the pattern (i.e. how strong the skinconductivity response will be), n and B are further scaling factors thatdetermine the gradient of the initial part of the pattern (i.e. howquickly the skin conductivity will increase), τ is a scaling factor thatdetermines the gradient of the part of the pattern after the initialpeak in the pattern (i.e. how quickly the skin conductivity returns tothe initial level) and DC_remove is the DC component excluded from thepattern.

This function is illustrated in FIG. 5 and shows that there is a largesteep increase in the skin conductivity measurement following astressful event, such as a fall, followed by a slow recovery, with A, n,B, τ and DC_remove taking the values, 1/150, 300, 3, 3 and 2respectively. It has been found that the recovery of skin conductivityhappens relatively quickly after normal emotional arousal, whereasrecovery is much longer after an event in which the person is scared orstressed, such as a fall. The recovery or decay in skin conductivityafter such an event can occur in two stages after the skin conductivitymaximum, with the decay coefficients differing by at least a factor of10. The y-axis in FIG. 5 has no unit, but it's scale is the same as theskin conductance measurement in FIG. 4( a) (i.e. a difference of 1 unitin the y-axis direction of FIG. 5 corresponds to a difference of 1Siemens difference in the y-axis direction in FIG. 4( a). An exemplaryoutput of the matched filtering process is shown in FIG. 4( c). It willbe appreciated that the values of A, n, B, τ and DC_remove can be variedfrom the exemplary values given above depending on available data(perhaps user-specific data) relating to the response of skinconductivity to a fall or other stress-inducing event. An optimizationtechnique, such as higher order degree polynomial regression, can beused to fit the curve of equation (1) to the available data.

It will also be appreciated by those skilled in the art that thepredetermined pattern can be represented by alternative functions tothat shown in equation (1). For example, any function that defines acurve having characteristics similar to that shown in FIG. 5 can be used(i.e. a sharp increase at the start, followed by a gradual recovery).Also, different curves can be used, with the processor 8 in the falldetector 2 selecting one for use based on the estimated severity of thefall. For example, where there is a high impact value deduced from theaccelerometer data, a response curve (predetermined pattern)corresponding to high tension can be used. In addition or alternatively,the predetermined pattern can be personalized to the user, sincedifferent people exhibit different skin conductivity levels andresponses to different events (although generally the differencesconcern the shape, rather than the magnitude).

The skin conductivity coefficients used in subsequent processing aredetermined by reversing the magnitude of the coefficients output by thematched filter (see FIG. 4( d)).

The processor 8 can then analyze the skin conductivity coefficients toprovide an indication of whether the user has potentially suffered afall (step 1097). In particular, the processor 8 can analyze thecoefficients within an analysis window that spans the skin conductivitymeasurements obtained during a predetermined period after an altitudedrop of more than a predetermined value has been observed. Thepredetermined period can be 15 seconds, although any suitable timeperiod can be used. The predetermined value for the altitude drop may be0.5 meters, although this value can be set based on user-specificparameters, such as the height of the user. An exemplary 15-secondanalysis window is shown in FIG. 6. It will be appreciated that in theembodiment where skin conductivity measurements are only collectedfollowing the detection of a change in altitude of at least 0.5 m or apossible impact, the analysis window will start effectively when theskin conductivity sensor starts to measure the skin conductivity (i.e.there will not be any data to the left of the analysis window in FIG.6).

In some embodiments, the processor 8 analyses the skin conductivitycoefficients in the analysis window by determining any one or more ofthe following: (i) the maximum value of the coefficients in the analysiswindow (ii) the mean of the coefficients in the analysis window, and/or(iii) the median of the coefficients in the analysis window. Theprocessor 8 can analyze individual ones of the features listed above todetermine if there has been a skin conductivity response consistent witha stressful event, such as a fall, having taken place, or multiple onesof the features listed above, for example by comparison of the featureswith respective thresholds. In that case, the processor 8 can determinewhether there has been a skin conductivity response based on acombination or a weighted combination of the derived features.

It will be appreciated that the final decision by the processor 8 onwhether the user has suffered a fall can be based on a combination orweighted combination of the results of the analysis of the measurementsfrom the movement sensor(s) 4, 6 and the analysis of the measurementsfrom the skin conductivity sensor 14.

In an alternative embodiment of the invention, a fall detector isprovided that determines if the user has potentially suffered a fallbased on measurements from a single sensor (specifically a skinconductivity sensor 14). In this embodiment, the measurements from theskin conductivity sensor 14 can be analyzed as described above toprovide an indication of whether the user has potentially suffered afall. Thus, the measurements of the skin conductivity are matched to apredetermined skin conductivity response corresponding to a stressfulevent to determine if the user has experienced such an event. Althoughthis fall detector may not necessarily be able to distinguish between afall and other types of stressful event that might be experienced by theuser, the analysis of the skin conductivity measurements described abovewould still allow stressful events (including falls) to be identifiedfrom other types of event (including normal emotional arousal) that leadto a or no significant change in skin conductivity. Although a falldetector according to this embodiment of the invention might providesome false positive indications (because non-fall stressful events arealso identified by the analysis of the skin conductivity measurements)this is still a useful embodiment since the rate of false negatives(i.e. where there would be no indication of a fall when in fact the userhas fallen) will be quite low.

There is therefore provided a method for detecting a potential fall anda fall detector that provides increased fall detection reliabilitycompared to conventional techniques.

While the invention has been illustrated and described in detail in thedrawings and foregoing description, such illustration and descriptionare to be considered illustrative or exemplary and not restrictive; theinvention is not limited to the disclosed embodiments.

Variations to the disclosed embodiments can be understood and effectedby those skilled in the art in practicing the claimed invention, from astudy of the drawings, the disclosure, and the appended claims. In theclaims, the word “comprising” does not exclude other elements or steps,and the indefinite article “a” or “an” does not exclude a plurality. Asingle processor or other unit may fulfill the functions of severalitems recited in the claims. The mere fact that certain measures arerecited in mutually different dependent claims does not indicate that acombination of these measures cannot be used to advantage. A computerprogram may be stored/distributed on a suitable medium, such as anoptical storage medium or a solid-state medium supplied together with oras part of other hardware, but may also be distributed in other forms,such as via the Internet or other wired or wireless telecommunicationsystems. Any reference signs in the claims should not be construed aslimiting the scope.

1. A fall detector for detecting a potential fall by a user, the fall detector comprising: a sensor for measuring the skin conductivity of the user; and a processor for analyzing the skin conductivity measurements to determine whether the user has had a potential fall, wherein the processor is configured to use a matched filter to match the skin conductivity measurements to a predetermined skin conductivity response corresponding to a stressful event to generate skin conductivity coefficients, the value of each coefficient indicating the match of a respective set of consecutive skin conductivity measurements to the predetermined skin conductivity response; and to determine whether the user has had a potential fall by analyzing the skin conductivity coefficients.
 2. (canceled)
 3. A fall detector as claimed in claim 1, wherein the processor is configured to analyze the skin conductivity coefficients to determine whether the skin conductivity measurements are consistent with a user having had a fall by determining one or more of (i) the maximum value of the coefficients, (ii) the mean of the coefficients, and/or (iii) the median of the coefficients.
 4. A fall detector as claimed in claim 1, wherein the processor is configured to filter the skin conductivity measurements to remove noise and/or interference prior to matching the skin conductivity measurements to the predetermined skin conductivity response.
 5. A fall detector as claimed in claim 4, wherein the processor is configured to use a median filter to remove the noise and/or interference from the skin conductivity measurements.
 6. A fall detector as claimed in claim 1, further comprising at least one movement sensor for sensing the movement of the user, the processor being further configured to analyze measurements from the at least one movement sensor to determine if the user may have fallen.
 7. A fall detector as claimed in claim 6, wherein the processor is configured to analyze the skin conductivity measurements only in the event that the measurements from the at least one movement sensor indicate that the user may have fallen.
 8. A fall detector as claimed in claim 6, wherein the processor is configured to use the skin conductivity sensor to measure the skin conductivity in the event that the measurements from the at least one movement sensor indicate that the user may have fallen.
 9. A fall detector as claimed in claim 6, wherein the processor is configured to analyze the skin conductivity measurements obtained during a time window following a time at which the measurements from the at least one sensor indicate that the user may have fallen.
 10. A method of detecting a potential fall by a user, the method comprising: measuring the skin conductivity of the user; and analyzing the skin conductivity measurements to determine whether the user has had a potential fall by using a matched filter to match the skin conductivity measurements to a predetermined skin conductivity response corresponding to a stressful event to generate skin conductivity coefficients, the value of each coefficient indicating the match of a respective set of consecutive skin conductivity measurements to the predetermined skin conductivity response, and determining whether the user has had a potential fall by analyzing the skin conductivity coefficients.
 11. (canceled)
 12. A method as claimed in claim 11, wherein analyzing the skin conductivity coefficients to determine whether the response is consistent with a user having had a fall comprises determining one or more of (i) the maximum value of the coefficients, (ii) the mean of the coefficients, and/or (iii) the median of the coefficients.
 13. A method as claimed in claim 10, further comprising the steps of: sensing the movement of the user; and analyzing the movement of the user to determine if the user may have fallen.
 14. A method as claimed in claim 13, wherein the step of analyzing the skin conductivity measurements is performed only in the event that the step of analyzing the movement of the user indicates that the user may have fallen.
 15. A computer program product comprising computer readable code embodied therein, the computer readable code being configured such that, upon execution by a suitable computer or processor, the computer or processor performs the method claimed of claim
 10. 